Background

Composite stacked material is widely used in many fields, such as aircraft, rocket, missile, and soon. In the process of drilling carbon fiber-reinforced polymer and titanium alloy lamination materials (CFRP/TC4, which is a typical structure in aircraft), tool wear is quick and serious, because the machining condition of the respective layers in stack is different.

Purpose

To ensure the drilling quality, drilling tool needs to be changed frequently. Therefore, if there is a detecting system in automatic drilling device to monitor and predict the tool wear effectively, it will help to improve the production efficiency and reduce the tool cost.

Methods

Based on the experiments of drilling CFRP/TC4 stacks, the acoustic emission (AE) signals were carefully analyzed using the method of statistical analysis, spectrum analysis, and wavelet packet.

Results

The results show that the root-mean-square value of the AE signals and the energy of the wavelet packet are correlated with the tool wear. Meanwhile, experiments indicate that chips and tool fracture will cause instantaneous signal mutation, which may be appeared as disturbances. This has increased the difficulty of identifying the tool wear.

Conclusion

With repeated experiments and comparison, it was found that the percentage of wavelet packet energy of some certain frequency sections increased with the tool wear, while some decreased. These variations will be possible to be used as features for further prediction in monitoring system.

中文翻译：

---

通过声发射检测钻井CFRP / TC4堆中的工具磨损

背景

复合堆叠材料广泛应用于许多领域，例如飞机，火箭，导弹以及不久的将来。在钻碳纤维增强的聚合物和钛合金层压材料（CFRP / TC4，这是飞机上的典型结构）的过程中，由于堆栈中各层的加工条件不同，因此工具磨损迅速而严重。

目的

为了保证钻孔质量，需要经常更换钻孔工具。因此，如果在自动钻孔装置中设有检测系统来有效地监测和预测刀具磨损，将有助于提高生产效率，降低刀具成本。

方法

在钻CFRP / TC4烟囱的实验的基础上，使用统计分析，频谱分析和小波包方法对声发射（AE）信号进行了仔细分析。

结果

结果表明，AE信号的均方根值和小波包的能量与刀具磨损相关。同时，实验表明，切屑和工具断裂会引起瞬时信号突变，可能会出现干扰。这增加了识别工具磨损的难度。

结论

经过反复的实验和比较，发现某些频率段的小波包能量百分比随工具磨损的增加而减小。这些变化将有可能用作监视系统中进一步预测的功能。